Advances in plasma processing have facilitated the growth in the semiconductor industry. Recipes have long been employed by the semiconductor industry to create new devices (e.g., MEMS, chips, etc.). Different recipes may be utilized to perform substrate processing. Recipes tend to be complex and are usually created based on the knowledge and/or experience of the engineers.
Consider the situation wherein, for example, a processing system has been deployed to a device manufacturer site. Further, the manufacturer of the processing system may have incorporated best known methods to aid the device manufacturer in the creation of recipes. The device manufacture may employ the best known methods to customize recipes. In addition, the customized recipes may also be based on the knowledge and experience of the device manufacture's engineers, empirical data, a trail and error method, and the likes.
Usually, a successful execution of a recipe may be dependent upon other variables beside the recipe. Other variables may include, but are not limited to, the condition of the wafers, the chamber condition of the processing system, the wafer environment, and the likes. As a result, the engineers not only have to be knowledgeable about the recipe but may also be required to understand how the recipe may interact with other variables, such as those aforementioned.
In an example, a recipe has been created and an engineer has employed the recipe to create a plurality of devices. During the execution of the recipe, a plurality of data may be collected. The data that may be collected may be a mass collection of data points. The ability to assimilate the data, to determine which data points are critical, and/or to analyze the data in order to modify the recipe may be dependent upon the skill and experience of the engineer. For example, the engineer may be required to understand the recipe and how the recipe may interact with other variables that may affect the execution of the recipe. Unfortunately, the skill level and experience of an engineer may vary and the ‘quality’ of a recipe may reflect accordingly. Even if the engineer has the skill and experience, the engineer may not be able to account for the different variables in the creation of a new recipe and/or the modification of a current recipe.
In another example, a problem may arise during the execution of a recipe. The ability to analyze the data in order to debug the problem may also be dependent upon the engineer's experience and his ability to pinpoint the problem given the different variables that may cause the problem. Traditionally, the problem that may arise is usually assumed to be a hardware issue. As a result, the processing system may be taken offline in order to debug the problem. However, the cause of the problem may not always be due to the processing system. For example, about 60 percent of the de-chuck problems that may arise during execution of a recipe is usually not a hardware issue, but instead, a result of a “bad recipe”. Unfortunately, by the time the processing system has been eliminated as a potential source of the problem and the recipe has been identified as the source of the problem, costly time and resources have been incurred.